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The Inverse of a Matrix
These entries stretch diagonally down the matrix,
from top left to bottom right.
8
The Inverse of a Matrix
Thus the 2  2, 3  3, and 4  4 identity matrices are
Identity matrices behave like the number 1 in the
sense that
A  In = A and In  B = B
whenever these products are defined.
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Example 1 – Identity Matrices
The following matrix products show how multiplying a
matrix by an identity matrix of the appropriate
dimension leaves the matrix unchanged.
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The Inverse of a Matrix
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Example 2 – Verifying That a Matrix Is an Inverse
Verify that B is the inverse of A, where
and
Solution:
We perform the matrix multiplications to show that AB = I
and BA = I.
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Example 2 – Solution cont’d

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Finding the Inverse
of a 2  2 Matrix
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Finding the Inverse of a 2  2 Matrix
The following rule provides a simple way for finding
the inverse of a 2  2 matrix, when it exists.
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Example 3 – Finding the Inverse of a 2  2 Matrix
Let
Find A–1, and verify that AA–1 = A–1A = I2.
Solution:
Using the rule for the inverse of a 2  2 matrix, we get
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Example 3 – Solution
To verify that this is indeed the inverse of A, we calculate
AA–1 and A–1A:
cont’d
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Example 3 – Solution cont’d
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Finding the Inverse of a 2  2 Matrix
The quantity ad – bc that appears in the rule for
calculating the inverse of a 2  2 matrix is called the
determinant of the matrix.
If the determinant is 0, then the matrix does not have
an inverse (since we cannot divide by 0).

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Finding the Inverse
of an n  n Matrix
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Finding the Inverse of an n  n Matrix
For 3  3 and larger square matrices the following
technique provides the most efficient way to calculate
their inverses.
If A is an n  n matrix, we first construct the n  2n
matrix that has the entries of A on the left and of the
identity matrix In on the right:
21
Finding the Inverse of an n  n Matrix
We then use the elementary row operations on this
new large matrix to change the left side into the
identity matrix. (This means that we are changing
the large matrix to reduced row-echelon form.)
The right side is transformed automatically into A–1.
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Example 4 – Finding the Inverse of a 3  3 Matrix
Let A be the matrix
(a) Find A–1.
(b) Verify that AA–1 = A–1A = I3.
Solution:
(a) We begin with the 3  6 matrix whose left half is A and
whose right half is the identity matrix.
23
Example 4 – Solution
Transform the left half of this new matrix into the identity
matrix by performing the following sequence of elementary
row operations on the entire new matrix.
cont’d
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Example 4 – Solution
We have now transformed the left half of this matrix into
an identity matrix. (This means that we have put the entire
matrix in reduced row-echelon form.)
Note that to do this in as systematic a fashion as possible,
we first changed the elements below the main diagonal to
zeros, just as we would if we were using Gaussian
elimination.
cont’d

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Example 4 – Solution
We then changed each main diagonal element to a 1 by
multiplying by the appropriate constant(s).
Finally, we completed the process by changing the remaining
entries on the left side to zeros.
The right half is now A–1.
cont’d
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Example 4 – Solution
We calculate AA–1 and A–1A and verify that both
products give the identity matrix I3.
cont’d
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Finding the Inverse of an n  n Matrix
If we encounter a row of zeros on
the left when trying to find an
inverse, then the original matrix
does not have an inverse.
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Matrix Equations
29
Matrix Equations
The system
x – 2y – 4z = 7
2x – 3y – 6z = 5
– -3x + 6y + 15z = 0
is equivalent to the matrix equation
30
Matrix Equations
If we let
then this matrix equation can be written as
AX = B
The matrix A is called the coefficient matrix.

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Matrix Equations
We solve this matrix equation by multiplying each side by
the inverse of A (provided that this inverse exists):
AX = B
A–1(AX) = A–1B
(A–1A)X = A–1B
I3 X = A–1B
X = A–1B
Multiply on left by A–1
Associative Property
Property of inverses
Property of identity matrix
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Matrix Equations
In Example 4 we showed that
So from X = A–1B we have
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Matrix Equations
Thus x = –11, y = –23, z = 7 is the solution of the original
system.
We have proved that the matrix equation AX = B can be
solved by the following method.
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Example 6 – Solving a System Using a Matrix Inverse
A system of equations is given.
(a) Write the system of equations as a matrix equation.
(b) Solve the system by solving the matrix equation.
2x – 5y = 15
3x – 6y = 36
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Example 6(a) – Solution
We write the system as a matrix equation of the form
AX = B.
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Example 6(b) – Solution
Using the rule for finding the inverse of a 2  2 matrix,
we get
cont’d

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Example 6(b) – Solution
Multiplying each side of the matrix equation by this inverse
matrix, we get
So x = 30 and y = 9.
cont’d